Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Sequential decision fusion of multibiometrics applied to text-dependent speaker verification for controlled errors

Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

Asset allocation policy, returns and expenses of superannuation funds : recent evidence based on default options

We examine the asset allocation, returns, and expenses of superannuation funds whose assets are mainly invested in default investment options between 2004 and 2012. A majority of these funds fail to earn returns commensurate with their strategic asset allocation policy. It appears that much of the variation of returns between the funds might be a result of their engaging in significant active management of assets. Our results indicate that returns from active management are negatively related to expenses. We also find strong evidence of economies of scale existing in these superannuation funds across different size categories.

Decision making under pressure : a behavioural economics perspective

This research investigates the decision making process of individuals from revealed preferences in extreme environments or life-and-death situations, from a behavioral economics perspective. The empirical analysis of revealed behavioral preferences shows how the individual decision making process can deviate from the standard self-interested or “homo economicus” model in non-standard situations. The environments examined include: elite athletes in FIFA World and Euro Cups; climbing on Everest and the Himalaya; communication during 9/11 and risk seeking after the 2011 Brisbane floods. The results reveal that the interaction of culture and environment has a significant impact on the decision process, as social behaviors and institutions are intimately intertwined, which govern the processes of human behavior and interaction. Additionally, that risk attitudes are not set and that immediate environmental factors can induce a significant shift in an individuals risk seeking behaviors.

Using strategically applied grazing to manage invasive alien plants in novel grasslands

Introduction Novel ecosystems that contain new combinations of invasive alien plants (IAPs) present a challenge for managers. Yet, control strategies that focus on the removal of the invasive species and/or restoring historical disturbance regimes often do not provide the best outcome for long-term control of IAPs and the promotion of more desirable plant species. Methods This study seeks to identify the primary drivers of grassland invasion to then inform management practices toward the restoration of native ecosystems. By revisiting both published and unpublished data from experiments and case studies within mainly an Australian context for native grassland management, we show how alternative states models can help to design control strategies to manage undesirable IAPs by manipulating grazing pressure. Results Ungulate grazing is generally considered antithetical to invasive species management because in many countries where livestock production is a relatively new disturbance to grasslands (such as in Australia and New Zealand as well as Canada and the USA), selective grazing pressure may have facilitated opportunities for IAPs to establish. We find that grazing stock can be used to manipulate species composition in favour of the desirable components in pastures, but whether grazing is rested or strategically applied depends on the management goal, sizes of populations of the IAP and more desirable species, and climatic and edaphic conditions. Conclusions Based on our findings, we integrated these relationships to develop a testable framework for managing IAPs with strategic grazing that considers both the current state of the plant community and the desired future state—i.e. the application of the principles behind reclamation, rehabilitation, restoration or all three—over time.

The increasing cost of healthy food

OBJECTIVE: To assess changes in the cost and availability of a standard basket of healthy food items (the Healthy Food Access Basket [HFAB]) in Queensland. METHODS: Analysis of five cross-sectional surveys (1998, 2000, 2001, 2004 and 2006) describes changes over time. Eighty-nine stores in five remoteness categories were surveyed during May 2006. For the first time a sampling framework based on randomisation of towns throughout the state was applied and the survey was conducted by Queensland Treasury. RESULTS: Compared with the costs in major cities, in 2006 the mean cost of the HFAB was $107.81 (24.2%) higher in very remote stores in Queensland, but $145.57 (32.6%) higher in stores more than 2,000 kilometres from Brisbane. Over six years the cost of the HFAB has increased by around 50% ($148.87) across Queensland and, where data was available, by more than the cost of less healthy alternatives. The Consumer Price Index for food in Brisbane increased by 32.5% over the same period. CONCLUSIONS AND IMPLICATIONS: Australians, no matter where they live, need access to affordable, healthy food. Issues of food security in the face of rising food costs are of concern particularly in the current global economic downturn. There is an urgent need to nationally monitor, but also sustainably address the factors affecting the price of healthy foods, particularly for vulnerable groups who suffer a disproportionate burden of poor health.

Public Economics and the Assessment of Tourism Developments and Policies

Public economics covers both topics in welfare economic of social (as opposed to private) interest and aspects of public finance. This chapter considers the application of two methods of social economic evaluation of tourist developments, namely, social cost-benefit analysis and economic impact analysis. The role of social cost-benefit analysis in the assessment of tourism is illustrated by its application to the evaluation of inbound tourism. This is followed by a discussion of taxes on tourism and subsidies to promote it. The principle focus is on hotel room taxes. The analysis of taxes on tourism involves both public finance and welfare economics issues. The scope for and desirability of applying the user-pays principle to tourism is then examined.

Systematic evaluation of GoSoapBox in tertiary education : a student response system for improving learning experiences and outcomes

There is currently a wide range of research into the recent introduction of student response systems in higher education and tertiary settings (Banks 2006; Kay and Le Sange, 2009; Beatty and Gerace 2009; Lantz 2010; Sprague and Dahl 2009). However, most of this pedagogical literature has generated ‘how to’ approaches regarding the use of ‘clickers’, keypads, and similar response technologies. There are currently no systematic reviews on the effectiveness of ‘GoSoapBox’ – a more recent, and increasingly popular student response system – for its capacity to enhance critical thinking, and achieve sustained learning outcomes. With rapid developments in teaching and learning technologies across all undergraduate disciplines, there is a need to obtain comprehensive, evidence-based advice on these types of technologies, their uses, and overall efficacy. This paper addresses this current gap in knowledge. Our teaching team, in an undergraduate Sociology and Public Health unit at the Queensland University of Technology (QUT), introduced GoSoapBox as a mechanism for discussing controversial topics, such as sexuality, gender, economics, religion, and politics during lectures, and to take opinion polls on social and cultural issues affecting human health. We also used this new teaching technology to allow students to interact with each other during class – both on both social and academic topics – and to generate discussions and debates during lectures. The paper reports on a data-driven study into how this interactive online tool worked to improve engagement and the quality of academic work produced by students. This paper will firstly, cover the recent literature reviewing student response systems in tertiary settings. Secondly, it will outline the theoretical framework used to generate this pedagogical research. In keeping with the social and collaborative features of Web 2.0 technologies, Bandura’s Social Learning Theory (SLT) will be applied here to investigate the effectiveness of GoSoapBox as an online tool for improving learning experiences and the quality of academic output by students. Bandura has emphasised the Internet as a tool for ‘self-controlled learning’ (Bandura 2001), as it provides the education sector with an opportunity to reconceptualise the relationship between learning and thinking (Glassman & Kang 2011). Thirdly, we describe the methods used to implement the use of GoSoapBox in our lectures and tutorials, and which aspects of the technology we drew on for learning purposes, as well as the methods for obtaining feedback from the students about the effectiveness or otherwise of this tool. Fourthly, we report cover findings from an examination of all student/staff activity on GoSoapBox as well as reports from students about the benefits and limitations of it as a learning aid. We then display a theoretical model that is produced via an iterative analytical process between SLT and our data analysis for use by academics and teachers across the undergraduate curriculum. The model has implications for all teachers considering the use of student response systems to improve the learning experiences of their students. Finally, we consider some of the negative aspects of GoSoapBox as a learning aid.

Current trends and issues in geographical education

In this introductory chapter to Schmeinck, D. and Lidstone, J. (2014) “Current trends and issues in geographical education” in Schmeinck, D. and Lidstone, J. (2014) Eds) Standards and Research in Geographical Education: Current Trends and International Issues. Berlin. Mensch und Buch Verlag. Pp. 5 - 16. , the authors review and analyse eleven papers originally presented to the Congress of the International Geographical Union held in Cologne in 2012. Taking the collection of papers as a single corpus representing the “state of the art” of geography education, they applied lexical and bibliometric analyses in an innovative attempt to identify the nature of geographical education as represented by this anthology of peer reviewed chapters presented at the start of the second decade of the Twenty-first century?

Graph coloring applied to secure computation in non-Abelian groups

We study the natural problem of secure n-party computation (in the computationally unbounded attack model) of circuits over an arbitrary finite non-Abelian group (G,⋅), which we call G-circuits. Besides its intrinsic interest, this problem is also motivating by a completeness result of Barrington, stating that such protocols can be applied for general secure computation of arbitrary functions. For flexibility, we are interested in protocols which only require black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our investigations focus on the passive adversarial model, where up to t of the n participating parties are corrupted.

Tomorrow's Technologies

Australian research and technological solutions are now being applied throughout the world.

Selecting volatility forecasting models for portfolio allocation purposes

Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.

Do left and right asymmetries of hemispheric preference interact with attention to predict local and global performance in applied tasks?

Many cognitive neuroscience studies show that the ability to attend to and identify global or local information is lateralised between the two hemispheres in the human brain; the left hemisphere is biased towards the local level, whereas the right hemisphere is biased towards the global level. Results of two studies show attention-focused people with a right ear preference (biased towards the left hemisphere) are better at local tasks, whereas people with a left ear preference (biased towards the right hemisphere) are better at more global tasks. In a third study we determined if right hemisphere-biased followers who attend to global stimuli are likely to have a stronger relationship between attention and globally based supervisor ratings of performance. Results provide evidence in support of this hypothesis. Our research supports our model and suggests that the interaction between attention and lateral preference is an important and novel predictor of work-related outcomes.